Welcome to the Cloud Commercial Communities monthly webinar and podcast update. Each month the team focuses on core programs, updates, trends, and technologies that Microsoft partners and customers need to know to increase success using Microsoft Azure and Dynamics.
Pharmaceutical companies need to meet demanding sales goals, manage intricate regulatory compliance, and maintain a competitive hold on the market.
One of the biggest challenges banks and financial service organizations face is the sheer volume involved with monitoring and managing thousands and thousands of loans. Events like weather, earthquakes, geo-economic swings, and political shifts make it difficult to analyze the impacts on capital reserves, service operations, and more.
Healthcare is drowning in data. Every patient brings a record that could span decades, with x-rays, MRIs, and other data that can affect every decision. Providers and payers bring their own…
Insurance companies that sell life, health, and property and casualty insurance are using machine learning (ML) to drive improvements in customer service, fraud detection, and operational efficiency. For example, the Azure cloud is helping insurance brands save time and effort using machine vision to assess damage in accidents, identify anomalies in billing, and more.
製造業を営む企業のお客様が IoT の導入を検討する際によく戸惑われているのが、IoT ベンダーやプラットフォームの数があまりに多いことです。IoT はまだ新しい分野で、流通するパーツや製品の多くが発展途上です。
Artificial Intelligence (AI) and Machine Learning (ML) are transforming healthcare. From streamlining operations to aiding in clinical diagnosis. Healthcare organizations are often challenged to begin an AI/ML journey due to lack of experience or high cost.
Technology is moving at an amazing pace. Manufacturers around the world are observing this first-hand. Additive manufacturing, robotics, and IoT are some of the technologies that directly influence…
At a previous position, I owned the software and hardware testing across a 6000-branch network for a large fortune 100 bank in the U.S. The complexity and sophistication of the end-to-end delivery of products and services to existing customers was daunting.
Artificial Intelligence (AI) and machine learning (ML) technologies extend the capabilities of software applications that are now found throughout our daily life: digital assistants, facial recognition, photo captioning, banking services, and product recommendations. The difficult part about integrating AI or ML into an application is not the technology, or the math, or the science or the algorithms.